Triple
T2839523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walgreens Boots Alliance |
E62430
|
entity |
| Predicate | operates |
P24
|
FINISHED |
| Object | Walgreens |
E62430
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Walgreens | Statement: [Walgreens Boots Alliance, operates, Walgreens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walgreens Context triple: [Walgreens Boots Alliance, operates, Walgreens]
-
A.
Walgreens Boots Alliance
chosen
Walgreens Boots Alliance is a major global pharmacy-led health and retail company that operates the Walgreens and Boots drugstore chains, among other health and beauty brands.
-
B.
CVS Health
CVS Health is a major American healthcare company that operates a large pharmacy chain and provides health insurance and pharmacy benefit management services.
-
C.
CVS
CVS is the IATA airport code for Cannon Air Force Base, a United States Air Force installation near Clovis, New Mexico.
-
D.
CVS
CVS (Concurrent Versions System) is an early, widely used open-source version control system that manages changes to source code in collaborative software development.
-
E.
Kroger
Kroger is one of the largest supermarket and retail grocery chains in the United States, operating thousands of stores under various banners nationwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdef145f08190be8556bc696ba3ab |
completed | March 7, 2026, 8:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8cf32d08190bda89a513082813f |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.